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. 2023 Dec;90(6):2539-2556.
doi: 10.1002/mrm.29817. Epub 2023 Aug 1.

A user independent denoising method for x-nuclei MRI and MRS

Nichlas Vous Christensen  1 , Michael Vaeggemose  1   2 , Nikolaj Bøgh  1   3 , Esben S S Hansen  1 , Jonas L Olesen  4 , Yaewon Kim  5 , Daniel B Vigneron  5 , Jeremy W Gordon  5 , Sune N Jespersen  4 , Christoffer Laustsen  1
Affiliations

A user independent denoising method for x-nuclei MRI and MRS

Nichlas Vous Christensen et al. Magn Reson Med. 2023 Dec.

Abstract

Purpose: X-nuclei (also called non-proton MRI) MRI and spectroscopy are limited by the intrinsic low SNR as compared to conventional proton imaging. Clinical translation of x-nuclei examination warrants the need of a robust and versatile tool improving image quality for diagnostic use. In this work, we compare a novel denoising method with fewer inputs to the current state-of-the-art denoising method.

Methods: Denoising approaches were compared on human acquisitions of sodium (23 Na) brain, deuterium (2 H) brain, carbon (13 C) heart and brain, and simulated dynamic hyperpolarized 13 C brain scans, with and without additional noise. The current state-of-the-art denoising method Global-local higher order singular value decomposition (GL-HOSVD) was compared to the few-input method tensor Marchenko-Pastur principal component analysis (tMPPCA). Noise-removal was quantified by residual distributions, and statistical analyses evaluated the differences in mean-square-error and Bland-Altman analysis to quantify agreement between original and denoised results of noise-added data.

Results: GL-HOSVD and tMPPCA showed similar performance for the variety of x-nuclei data analyzed in this work, with tMPPCA removing ˜5% more noise on average over GL-HOSVD. The mean ratio between noise-added and denoising reproducibility coefficients of the Bland-Altman analysis when compared to the original are also similar for the two methods with 3.09 ± 1.03 and 2.83 ± 0.79 for GL-HOSVD and tMPPCA, respectively.

Conclusion: The strength of tMPPCA lies in the few-input approach, which generalizes well to different data sources. This makes the use of tMPPCA denoising a robust and versatile tool in x-nuclei imaging improvements and the preferred denoising method.

Keywords: Denoising; MRI; deuterium; hyperpolarized carbon-13; sodium.

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